One common problem in flow cytometry is the necessity for coincidence detection in the presence of multiple particles that are closely spaced or joined in the sample. These closely spaced or joined particles are know as “doublets” when two particles are together or “higher-order aggregate particles” when three or more particles are together. Users of flow cytometry systems typically want to know if the sample contains aggregate particles. Depending on the experiment, aggregate particles can either be undesirable (such as contaminants from poor sample preparation) or desirable (such as cells in the process of cell division/mitosis).
Conventional flow cytometry systems operate with a user interface that may include a doublet discrimination module (DDM) feature. When this feature is activated, the detection system can detect closely spaced or joined particles, known in the art as “doublets”, via an algorithm that can recognize the characteristic “peak-trough-peak” waveform produced by doublets. When a doublet event is detected, the DDM artificially increases at least one of the parameter values to help the user more easily visualize and gate these events. This modification is not desirable, however, because the data is not preserved exactly as it was originally generated.
The limitations of the detection system and user interface of typical flow cytometer systems with a DDM feature have at least two disadvantages: (1) the potential loss of valuable original data because the DDM artificially increases at least one of the parameter values, modifying the data at the time of acquisition; and (2) the inability to observe and “undo” changes made to the data by the DDM without running additional samples.
Accordingly, there is a need in the art to create a new and improved detection system and user interface for a flow cytometer that avoids or minimizes these disadvantages. The present invention provides such new and improved detection system for a flow cytometer.